Self-healing infrastructure for a dual-database system

ABSTRACT

A database system could include a first database engine, a second database engine, and a replication engine. The database system could also include processors configured to perform operations. The operations could involve obtaining indicators that are respectively associated with performance issues that can occur in the database system, each indicator defining one or more conditions that, when satisfied, cause the indicator to become active. The operations could also involve obtaining mappings between: (i) at least some of the indicators, and (ii) remediation subroutines. The operations could additionally involve receiving operational data related to the first database engine, the second database engine, or the replication engine; determining, based on the operational data and the conditions defined by the indicators, that a particular indicator is active; determining, based on the mappings, that the particular indicator has an associated remediation subroutine; and executing the associated remediation subroutine.

BACKGROUND

A computational instance may be disposed within a remote networkmanagement platform and may be dedicated to a managed network. Thecomputational instance may store data related to the managed network,for example, in an authoritative database that acts as a single sourceof truth for the managed network.

During operations, users from the managed network may request data fromthe computational instance. These data requests could take the form ofdatabase queries that retrieve various pieces of information from theauthoritative database. However, if the authoritative database containsa large amount of records, perhaps millions or even billions of records,then the database queries could experience severe delays. This in turncould negatively affect the overall experience of the users.

SUMMARY

To reduce database query delays, a computational instance could put intooperation a dual-database system. Such a system may contain a firstdatabase engine and a second database engine. The first database enginecould be an authoritative database for the dual-database system. Thesecond database engine could be a read-only replica of the firstdatabase engine and could be configured with a technology that allowsfor efficient querying. For example, the second database engine could beconfigured as a column-oriented database engine.

During operations, a routing engine could receive database queries andappropriately route the queries to either the first database engine orthe second database engine. If a database query requires a fast responsetime, for example, in order to display information on a web page, thenthe routing engine may route the query to the second database engine. Onthe other hand, if a database query does not require a fast responsetime but instead requires authoritative data, for example, in order togenerate a financial audit report, then the routing engine may route thequery to the first database engine.

The dual-database system could also contain other components. Forexample, the dual-database system could include a replication enginethat replicates data from the first database engine to the seconddatabase engine. Additionally, the dual-database system could include adefragmentation engine that defragments data added to the seconddatabase engine by the replication engine. Other components may alsoexist.

Despite best efforts on the part of software engineers, software systemsare never foolproof. Thus, at times, the dual-database system couldexperience performance issues that cause it to perform sub-optimally orbehave in an unintended way. For example, the dual-database system mayinadvertently shut down, reject incoming database queries, or produceincorrect outputs, among other possibilities. Such performance issuesmay result, for example, from a software defect in the components in thedual-database system.

Upon discovering a performance issue, a user could submit a supportticket to an entity associated with the dual-database system. An agentfrom the entity may be assigned to troubleshoot the performance issueraised by the ticket. In a typical troubleshooting process, the assignedagent may examine portions of dual-database system in an attempt toidentify the components of the dual-database system that might encompassthe performance issue. For instance, the assigned agent may examine logfiles, application source code files, and the like. Yet, if the assignedagent is not otherwise familiar with aspects of the dual-databasesystem, this troubleshooting process can become overly complex and timeconsuming. Further, even after identifying the components that encompassthe performance issue, formulating an appropriate response to get thedual-database system fully restored may take days or even weeks, as theagent may have limited resources with which to address the performanceissue. And through all that time, the dual-database system may beperforming sub-optimally and the user's activities may be negativelyimpacted.

Disclosed herein is an approach to address this technical problem. Inaccordance with the disclosure, a computational instance may include aninfrastructure remediation tool that can pinpoint and automaticallyresolve performance issues in a dual-database system. The infrastructureremediation could have access to operational data from each of thecomponents of the dual-database system. Additionally, the infrastructureremediation tool could be configured with a set of performance issueindicators, each indicator containing one or more conditions. If theoperational data from the dual-database system satisfies the conditionsfor a performance issue indicator, the infrastructure remediation toolcould determine that that indicator is “active.” Otherwise, if theoperational data from the dual-database system does not satisfy theconditions for a performance issue indicator, the infrastructureremediation tool could determine that that indicator is “inactive.”

The infrastructure remediation tool could also be configured withmappings between performance issue indicators and subroutines that canbe executed by the computational instance to remedy the correspondingperformance issues raised by the indicators. Accordingly, upondetermining that an indicator is active, the infrastructure remediationtool could refer to the mappings to determine an appropriate subroutinethat will remedy the performance issue raised by the indicator. Theinfrastructure remediation tool could then execute that subroutine.After executing the subroutine, the infrastructure remediation toolcould establish whether the subroutine actually succeeded in remediatingthe performance issue by determining if the indicator is still active.If the subroutine did not succeed, the infrastructure remediation toolmay escalate the performance issue to an assigned agent. Given that adual-database system could experience hundreds, if not thousands ofperformance issues, the disclosed infrastructure remediation tooladvantageously allows dual-database systems to remediate performanceissues without the need for external assistance, and thus allowing thedual-database system to “self-heal.” Further, the disclosedinfrastructure remediation tool also reduces the number of performanceissues that are escalated to agents, thereby allowing the agents tofocus on other, potentially higher-level issues. Other advantages mayalso exist.

Accordingly, a first example embodiment may involve a database system.The database system could include a first database engine, a seconddatabase engine, and a replication engine configured to perform: (i) areplication process to replicate entries from the first database engineto the second database engine, and (ii) a defragmentation process todefragment the entries that are in the second database engine. Thedatabase system could also include one or more processors configured toperform operations. The operations could involve obtaining a set ofindicators that are respectively associated with performance issues thatcan occur in the database system. Each respective indicator may defineone or more conditions that, when satisfied, cause the respectiveindicator to become active. The one or more conditions may relate to thefirst database engine, the second database engine, the replicationengine, the replication process, or the defragmentation process. Theoperations could also involve obtaining a set of mappings between: (i)at least some of the set of indicators, and (ii) remediationsubroutines. The operations could additionally involve receivingoperational data related to one or more of the first database engine,the second database engine, the replication engine, the replicationprocess, or the defragmentation process. The operations could furtherinvolve determining, based on the operational data and the conditionsdefined by the set of indicators, that a particular indicator is active.The operations could yet further involve, responsive to the particularindicator being active, determining, based on the set of mappings, thatthe particular indicator has an associated remediation subroutine. Theoperations could also involve executing the associated remediationsubroutine.

In a second example embodiment, an article of manufacture may include anon-transitory computer-readable medium, having stored thereon programinstructions that, upon execution by a computing system, cause thecomputing system to perform operations in accordance with the firstexample embodiment.

In a third example embodiment, a computing system may include at leastone processor, as well as memory and program instructions. The programinstructions may be stored in the memory, and upon execution by the atleast one processor, cause the computing system to perform operations inaccordance with the first example embodiment.

In a fourth example embodiment, a system may include various means forcarrying out each of the operations of the first example embodiment.

These, as well as other embodiments, aspects, advantages, andalternatives, will become apparent to those of ordinary skill in the artby reading the following detailed description, with reference whereappropriate to the accompanying drawings. Further, this summary andother descriptions and figures provided herein are intended toillustrate embodiments by way of example only and, as such, thatnumerous variations are possible. For instance, structural elements andprocess steps can be rearranged, combined, distributed, eliminated, orotherwise changed, while remaining within the scope of the embodimentsas claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a schematic drawing of a computing device, inaccordance with example embodiments.

FIG. 2 illustrates a schematic drawing of a server device cluster, inaccordance with example embodiments.

FIG. 3 depicts a remote network management architecture, in accordancewith example embodiments.

FIG. 4 depicts a communication environment involving a remote networkmanagement architecture, in accordance with example embodiments.

FIG. 5A depicts another communication environment involving a remotenetwork management architecture, in accordance with example embodiments.

FIG. 5B is a flow chart, in accordance with example embodiments.

FIG. 6 depicts a network architecture, in accordance with exampleembodiments.

FIG. 7 depicts elements of a performance issue indicator, in accordancewith example embodiments

FIG. 8 depicts a table of performance issue indicators, in accordancewith example embodiments.

FIG. 9 depicts mappings between performance issue indicators andsubroutines, in accordance with example embodiments.

FIG. 10 is a flow chart illustrating example operations of aninfrastructure remediation tool, in accordance with example embodiments.

FIG. 11 depicts a message flow, in accordance with example embodiments.

FIG. 12 is a flow chart, in accordance with example embodiments.

DETAILED DESCRIPTION

Example methods, devices, and systems are described herein. It should beunderstood that the words “example” and “exemplary” are used herein tomean “serving as an example, instance, or illustration.” Any embodimentor feature described herein as being an “example” or “exemplary” is notnecessarily to be construed as preferred or advantageous over otherembodiments or features unless stated as such. Thus, other embodimentscan be utilized and other changes can be made without departing from thescope of the subject matter presented herein.

Accordingly, the example embodiments described herein are not meant tobe limiting. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe figures, can be arranged, substituted, combined, separated, anddesigned in a wide variety of different configurations. For example, theseparation of features into “client” and “server” components may occurin a number of ways.

Further, unless context suggests otherwise, the features illustrated ineach of the figures may be used in combination with one another. Thus,the figures should be generally viewed as component aspects of one ormore overall embodiments, with the understanding that not allillustrated features are necessary for each embodiment.

Additionally, any enumeration of elements, blocks, or steps in thisspecification or the claims is for purposes of clarity. Thus, suchenumeration should not be interpreted to require or imply that theseelements, blocks, or steps adhere to a particular arrangement or arecarried out in a particular order.

Introduction

A large enterprise is a complex entity with many interrelatedoperations. Some of these are found across the enterprise, such as humanresources (HR), supply chain, information technology (IT), and finance.However, each enterprise also has its own unique operations that provideessential capabilities and/or create competitive advantages.

To support widely-implemented operations, enterprises typically useoff-the-shelf software applications, such as customer relationshipmanagement (CRM) and human capital management (HCM) packages. However,they may also need custom software applications to meet their own uniquerequirements. A large enterprise often has dozens or hundreds of thesecustom software applications. Nonetheless, the advantages provided bythe embodiments herein are not limited to large enterprises and may beapplicable to an enterprise, or any other type of organization, of anysize.

Many such software applications are developed by individual departmentswithin the enterprise. These range from simple spreadsheets tocustom-built software tools and databases. But the proliferation ofsiloed custom software applications has numerous disadvantages. Itnegatively impacts an enterprise's ability to run and grow itsoperations, innovate, and meet regulatory requirements. The enterprisemay find it difficult to integrate, streamline, and enhance itsoperations due to lack of a single system that unifies its subsystemsand data.

To efficiently create custom applications, enterprises would benefitfrom a remotely-hosted application platform that eliminates unnecessarydevelopment complexity. The goal of such a platform would be to reducetime-consuming, repetitive application development tasks so thatsoftware engineers and individuals in other roles can focus ondeveloping unique, high-value features.

In order to achieve this goal, the concept of Application Platform as aService (aPaaS) is introduced, to intelligently automate workflowsthroughout the enterprise. An aPaaS system is hosted remotely from theenterprise, but may access data, applications, and services within theenterprise by way of secure connections. Such an aPaaS system may have anumber of advantageous capabilities and characteristics. Theseadvantages and characteristics may be able to improve the enterprise'soperations and workflows for IT, HR, CRM, customer service, applicationdevelopment, and security.

The aPaaS system may support development and execution ofmodel-view-controller (MVC) applications. MVC applications divide theirfunctionality into three interconnected parts (model, view, andcontroller) in order to isolate representations of information from themanner in which the information is presented to the user, therebyallowing for efficient code reuse and parallel development. Theseapplications may be web-based, and offer create, read, update, delete(CRUD) capabilities. This allows new applications to be built on acommon application infrastructure.

The aPaaS system may support standardized application components, suchas a standardized set of widgets for graphical user interface (GUI)development. In this way, applications built using the aPaaS system havea common look and feel. Other software components and modules may bestandardized as well. In some cases, this look and feel can be brandedor skinned with an enterprise's custom logos and/or color schemes.

The aPaaS system may support the ability to configure the behavior ofapplications using metadata. This allows application behaviors to berapidly adapted to meet specific needs. Such an approach reducesdevelopment time and increases flexibility. Further, the aPaaS systemmay support GUI tools that facilitate metadata creation and management,thus reducing errors in the metadata.

The aPaaS system may support clearly-defined interfaces betweenapplications, so that software developers can avoid unwantedinter-application dependencies. Thus, the aPaaS system may implement aservice layer in which persistent state information and other data arestored.

The aPaaS system may support a rich set of integration features so thatthe applications thereon can interact with legacy applications andthird-party applications. For instance, the aPaaS system may support acustom employee-onboarding system that integrates with legacy HR, IT,and accounting systems.

The aPaaS system may support enterprise-grade security. Furthermore,since the aPaaS system may be remotely hosted, it should also utilizesecurity procedures when it interacts with systems in the enterprise orthird-party networks and services hosted outside of the enterprise. Forexample, the aPaaS system may be configured to share data amongst theenterprise and other parties to detect and identify common securitythreats.

Other features, functionality, and advantages of an aPaaS system mayexist. This description is for purpose of example and is not intended tobe limiting.

As an example of the aPaaS development process, a software developer maybe tasked to create a new application using the aPaaS system. First, thedeveloper may define the data model, which specifies the types of datathat the application uses and the relationships therebetween. Then, viaa GUI of the aPaaS system, the developer enters (e.g., uploads) the datamodel. The aPaaS system automatically creates all of the correspondingdatabase tables, fields, and relationships, which can then be accessedvia an object-oriented services layer.

In addition, the aPaaS system can also build a fully-functional MVCapplication with client-side interfaces and server-side CRUD logic. Thisgenerated application may serve as the basis of further development forthe user. Advantageously, the developer does not have to spend a largeamount of time on basic application functionality. Further, since theapplication may be web-based, it can be accessed from anyInternet-enabled client device. Alternatively or additionally, a localcopy of the application may be able to be accessed, for instance, whenInternet service is not available.

The aPaaS system may also support a rich set of pre-definedfunctionality that can be added to applications. These features includesupport for searching, email, templating, workflow design, reporting,analytics, social media, scripting, mobile-friendly output, andcustomized GUIs.

Such an aPaaS system may represent a GUI in various ways. For example, aserver device of the aPaaS system may generate a representation of a GUIusing a combination of HTML and JAVASCRIPT®. The JAVASCRIPT® may includeclient-side executable code, server-side executable code, or both. Theserver device may transmit or otherwise provide this representation to aclient device for the client device to display on a screen according toits locally-defined look and feel. Alternatively, a representation of aGUI may take other forms, such as an intermediate form (e.g., JAVA®byte-code) that a client device can use to directly generate graphicaloutput therefrom. Other possibilities exist.

Further, user interaction with GUI elements, such as buttons, menus,tabs, sliders, checkboxes, toggles, etc. may be referred to as“selection”, “activation”, or “actuation” thereof. These terms may beused regardless of whether the GUI elements are interacted with by wayof keyboard, pointing device, touchscreen, or another mechanism.

An aPaaS architecture is particularly powerful when integrated with anenterprise's network and used to manage such a network. The followingembodiments describe architectural and functional aspects of exampleaPaaS systems, as well as the features and advantages thereof.

II. Example Computing Devices and Cloud-Based Computing Environments

FIG. 1 is a simplified block diagram exemplifying a computing device100, illustrating some of the components that could be included in acomputing device arranged to operate in accordance with the embodimentsherein. Computing device 100 could be a client device (e.g., a deviceactively operated by a user), a server device (e.g., a device thatprovides computational services to client devices), or some other typeof computational platform. Some server devices may operate as clientdevices from time to time in order to perform particular operations, andsome client devices may incorporate server features.

In this example, computing device 100 includes processor 102, memory104, network interface 106, and input/output unit 108, all of which maybe coupled by system bus 110 or a similar mechanism. In someembodiments, computing device 100 may include other components and/orperipheral devices (e.g., detachable storage, printers, and so on).

Processor 102 may be one or more of any type of computer processingelement, such as a central processing unit (CPU), a co-processor (e.g.,a mathematics, graphics, or encryption co-processor), a digital signalprocessor (DSP), a network processor, and/or a form of integratedcircuit or controller that performs processor operations. In some cases,processor 102 may be one or more single-core processors. In other cases,processor 102 may be one or more multi-core processors with multipleindependent processing units. Processor 102 may also include registermemory for temporarily storing instructions being executed and relateddata, as well as cache memory for temporarily storing recently-usedinstructions and data.

Memory 104 may be any form of computer-usable memory, including but notlimited to random access memory (RAM), read-only memory (ROM), andnon-volatile memory (e.g., flash memory, hard disk drives, solid statedrives, compact discs (CDs), digital video discs (DVDs), and/or tapestorage). Thus, memory 104 represents both main memory units, as well aslong-term storage. Other types of memory may include biological memory.

Memory 104 may store program instructions and/or data on which programinstructions may operate. By way of example, memory 104 may store theseprogram instructions on a non-transitory, computer-readable medium, suchthat the instructions are executable by processor 102 to carry out anyof the methods, processes, or operations disclosed in this specificationor the accompanying drawings.

As shown in FIG. 1, memory 104 may include firmware 104A, kernel 104B,and/or applications 104C. Firmware 104A may be program code used to bootor otherwise initiate some or all of computing device 100. Kernel 104Bmay be an operating system, including modules for memory management,scheduling and management of processes, input/output, and communication.Kernel 104B may also include device drivers that allow the operatingsystem to communicate with the hardware modules (e.g., memory units,networking interfaces, ports, and buses) of computing device 100.Applications 104C may be one or more user-space software programs, suchas web browsers or email clients, as well as any software libraries usedby these programs. Memory 104 may also store data used by these andother programs and applications.

Network interface 106 may take the form of one or more wirelineinterfaces, such as Ethernet (e.g., Fast Ethernet, Gigabit Ethernet, andso on). Network interface 106 may also support communication over one ormore non-Ethernet media, such as coaxial cables or power lines, or overwide-area media, such as Synchronous Optical Networking (SONET) ordigital subscriber line (DSL) technologies. Network interface 106 mayadditionally take the form of one or more wireless interfaces, such asIEEE 802.11 (Wifi), BLUETOOTH®, global positioning system (GPS), or awide-area wireless interface. However, other forms of physical layerinterfaces and other types of standard or proprietary communicationprotocols may be used over network interface 106. Furthermore, networkinterface 106 may comprise multiple physical interfaces. For instance,some embodiments of computing device 100 may include Ethernet,BLUETOOTH®, and Wifi interfaces.

Input/output unit 108 may facilitate user and peripheral deviceinteraction with computing device 100. Input/output unit 108 may includeone or more types of input devices, such as a keyboard, a mouse, a touchscreen, and so on. Similarly, input/output unit 108 may include one ormore types of output devices, such as a screen, monitor, printer, and/orone or more light emitting diodes (LEDs). Additionally or alternatively,computing device 100 may communicate with other devices using auniversal serial bus (USB) or high-definition multimedia interface(HDMI) port interface, for example.

In some embodiments, one or more computing devices like computing device100 may be deployed to support an aPaaS architecture. The exact physicallocation, connectivity, and configuration of these computing devices maybe unknown and/or unimportant to client devices. Accordingly, thecomputing devices may be referred to as “cloud-based” devices that maybe housed at various remote data center locations.

FIG. 2 depicts a cloud-based server cluster 200 in accordance withexample embodiments. In FIG. 2, operations of a computing device (e.g.,computing device 100) may be distributed between server devices 202,data storage 204, and routers 206, all of which may be connected bylocal cluster network 208. The number of server devices 202, datastorages 204, and routers 206 in server cluster 200 may depend on thecomputing task(s) and/or applications assigned to server cluster 200.

For example, server devices 202 can be configured to perform variouscomputing tasks of computing device 100. Thus, computing tasks can bedistributed among one or more of server devices 202. To the extent thatthese computing tasks can be performed in parallel, such a distributionof tasks may reduce the total time to complete these tasks and return aresult. For purposes of simplicity, both server cluster 200 andindividual server devices 202 may be referred to as a “server device.”This nomenclature should be understood to imply that one or moredistinct server devices, data storage devices, and cluster routers maybe involved in server device operations.

Data storage 204 may be data storage arrays that include drive arraycontrollers configured to manage read and write access to groups of harddisk drives and/or solid state drives. The drive array controllers,alone or in conjunction with server devices 202, may also be configuredto manage backup or redundant copies of the data stored in data storage204 to protect against drive failures or other types of failures thatprevent one or more of server devices 202 from accessing units of datastorage 204. Other types of memory aside from drives may be used.

Routers 206 may include networking equipment configured to provideinternal and external communications for server cluster 200. Forexample, routers 206 may include one or more packet-switching and/orrouting devices (including switches and/or gateways) configured toprovide (i) network communications between server devices 202 and datastorage 204 via local cluster network 208, and/or (ii) networkcommunications between server cluster 200 and other devices viacommunication link 210 to network 212.

Additionally, the configuration of routers 206 can be based at least inpart on the data communication requirements of server devices 202 anddata storage 204, the latency and throughput of the local clusternetwork 208, the latency, throughput, and cost of communication link210, and/or other factors that may contribute to the cost, speed,fault-tolerance, resiliency, efficiency, and/or other design goals ofthe system architecture.

As a possible example, data storage 204 may include any form ofdatabase, such as a structured query language (SQL) database. Varioustypes of data structures may store the information in such a database,including but not limited to tables, arrays, lists, trees, and tuples.Furthermore, any databases in data storage 204 may be monolithic ordistributed across multiple physical devices.

Server devices 202 may be configured to transmit data to and receivedata from data storage 204. This transmission and retrieval may take theform of SQL queries or other types of database queries, and the outputof such queries, respectively. Additional text, images, video, and/oraudio may be included as well. Furthermore, server devices 202 mayorganize the received data into web page or web applicationrepresentations. Such a representation may take the form of a markuplanguage, such as the hypertext markup language (HTML), the extensiblemarkup language (XML), or some other standardized or proprietary format.Moreover, server devices 202 may have the capability of executingvarious types of computerized scripting languages, such as but notlimited to Perl, Python, PHP Hypertext Preprocessor (PHP), Active ServerPages (ASP), JAVASCRIPT®, and so on. Computer program code written inthese languages may facilitate the providing of web pages to clientdevices, as well as client device interaction with the web pages.Alternatively or additionally, JAVA® may be used to facilitategeneration of web pages and/or to provide web application functionality.

III. Example Remote Network Management Architecture

FIG. 3 depicts a remote network management architecture, in accordancewith example embodiments. This architecture includes three maincomponents—managed network 300, remote network management platform 320,and public cloud networks 340—all connected by way of Internet 350.

A. Managed Networks

Managed network 300 may be, for example, an enterprise network used byan entity for computing and communications tasks, as well as storage ofdata. Thus, managed network 300 may include client devices 302, serverdevices 304, routers 306, virtual machines 308, firewall 310, and/orproxy servers 312. Client devices 302 may be embodied by computingdevice 100, server devices 304 may be embodied by computing device 100or server cluster 200, and routers 306 may be any type of router,switch, or gateway.

Virtual machines 308 may be embodied by one or more of computing device100 or server cluster 200. In general, a virtual machine is an emulationof a computing system, and mimics the functionality (e.g., processor,memory, and communication resources) of a physical computer. Onephysical computing system, such as server cluster 200, may support up tothousands of individual virtual machines. In some embodiments, virtualmachines 308 may be managed by a centralized server device orapplication that facilitates allocation of physical computing resourcesto individual virtual machines, as well as performance and errorreporting. Enterprises often employ virtual machines in order toallocate computing resources in an efficient, as needed fashion.Providers of virtualized computing systems include VMWARE® andMICROSOFT®.

Firewall 310 may be one or more specialized routers or server devicesthat protect managed network 300 from unauthorized attempts to accessthe devices, applications, and services therein, while allowingauthorized communication that is initiated from managed network 300.Firewall 310 may also provide intrusion detection, web filtering, virusscanning, application-layer gateways, and other applications orservices. In some embodiments not shown in FIG. 3, managed network 300may include one or more virtual private network (VPN) gateways withwhich it communicates with remote network management platform 320 (seebelow).

Managed network 300 may also include one or more proxy servers 312. Anembodiment of proxy servers 312 may be a server application thatfacilitates communication and movement of data between managed network300, remote network management platform 320, and public cloud networks340. In particular, proxy servers 312 may be able to establish andmaintain secure communication sessions with one or more computationalinstances of remote network management platform 320. By way of such asession, remote network management platform 320 may be able to discoverand manage aspects of the architecture and configuration of managednetwork 300 and its components. Possibly with the assistance of proxyservers 312, remote network management platform 320 may also be able todiscover and manage aspects of public cloud networks 340 that are usedby managed network 300.

Firewalls, such as firewall 310, typically deny all communicationsessions that are incoming by way of Internet 350, unless such a sessionwas ultimately initiated from behind the firewall (i.e., from a deviceon managed network 300) or the firewall has been explicitly configuredto support the session. By placing proxy servers 312 behind firewall 310(e.g., within managed network 300 and protected by firewall 310), proxyservers 312 may be able to initiate these communication sessions throughfirewall 310. Thus, firewall 310 might not have to be specificallyconfigured to support incoming sessions from remote network managementplatform 320, thereby avoiding potential security risks to managednetwork 300.

In some cases, managed network 300 may consist of a few devices and asmall number of networks. In other deployments, managed network 300 mayspan multiple physical locations and include hundreds of networks andhundreds of thousands of devices. Thus, the architecture depicted inFIG. 3 is capable of scaling up or down by orders of magnitude.

Furthermore, depending on the size, architecture, and connectivity ofmanaged network 300, a varying number of proxy servers 312 may bedeployed therein. For example, each one of proxy servers 312 may beresponsible for communicating with remote network management platform320 regarding a portion of managed network 300. Alternatively oradditionally, sets of two or more proxy servers may be assigned to sucha portion of managed network 300 for purposes of load balancing,redundancy, and/or high availability.

B. Remote Network Management Platforms

Remote network management platform 320 is a hosted environment thatprovides aPaaS services to users, particularly to the operator ofmanaged network 300. These services may take the form of web-basedportals, for example, using the aforementioned web-based technologies.Thus, a user can securely access remote network management platform 320from, for example, client devices 302, or potentially from a clientdevice outside of managed network 300. By way of the web-based portals,users may design, test, and deploy applications, generate reports, viewanalytics, and perform other tasks.

As shown in FIG. 3, remote network management platform 320 includes fourcomputational instances 322, 324, 326, and 328. Each of thesecomputational instances may represent one or more server nodes operatingdedicated copies of the aPaaS software and/or one or more databasenodes. The arrangement of server and database nodes on physical serverdevices and/or virtual machines can be flexible and may vary based onenterprise needs. In combination, these nodes may provide a set of webportals, services, and applications (e.g., a wholly-functioning aPaaSsystem) available to a particular enterprise. In some cases, a singleenterprise may use multiple computational instances.

For example, managed network 300 may be an enterprise customer of remotenetwork management platform 320, and may use computational instances322, 324, and 326. The reason for providing multiple computationalinstances to one customer is that the customer may wish to independentlydevelop, test, and deploy its applications and services. Thus,computational instance 322 may be dedicated to application developmentrelated to managed network 300, computational instance 324 may bededicated to testing these applications, and computational instance 326may be dedicated to the live operation of tested applications andservices. A computational instance may also be referred to as a hostedinstance, a remote instance, a customer instance, or by some otherdesignation. Any application deployed onto a computational instance maybe a scoped application, in that its access to databases within thecomputational instance can be restricted to certain elements therein(e.g., one or more particular database tables or particular rows withinone or more database tables).

For purposes of clarity, the disclosure herein refers to the arrangementof application nodes, database nodes, aPaaS software executing thereon,and underlying hardware as a “computational instance.” Note that usersmay colloquially refer to the graphical user interfaces provided therebyas “instances.” But unless it is defined otherwise herein, a“computational instance” is a computing system disposed within remotenetwork management platform 320.

The multi-instance architecture of remote network management platform320 is in contrast to conventional multi-tenant architectures, overwhich multi-instance architectures exhibit several advantages. Inmulti-tenant architectures, data from different customers (e.g.,enterprises) are comingled in a single database. While these customers'data are separate from one another, the separation is enforced by thesoftware that operates the single database. As a consequence, a securitybreach in this system may impact all customers' data, creatingadditional risk, especially for entities subject to governmental,healthcare, and/or financial regulation. Furthermore, any databaseoperations that impact one customer will likely impact all customerssharing that database. Thus, if there is an outage due to hardware orsoftware errors, this outage affects all such customers. Likewise, ifthe database is to be upgraded to meet the needs of one customer, itwill be unavailable to all customers during the upgrade process. Often,such maintenance windows will be long, due to the size of the shareddatabase.

In contrast, the multi-instance architecture provides each customer withits own database in a dedicated computing instance. This preventscomingling of customer data, and allows each instance to beindependently managed. For example, when one customer's instanceexperiences an outage due to errors or an upgrade, other computationalinstances are not impacted. Maintenance down time is limited because thedatabase only contains one customer's data. Further, the simpler designof the multi-instance architecture allows redundant copies of eachcustomer database and instance to be deployed in a geographicallydiverse fashion. This facilitates high availability, where the liveversion of the customer's instance can be moved when faults are detectedor maintenance is being performed.

In some embodiments, remote network management platform 320 may includeone or more central instances, controlled by the entity that operatesthis platform. Like a computational instance, a central instance mayinclude some number of application and database nodes disposed upon somenumber of physical server devices or virtual machines. Such a centralinstance may serve as a repository for specific configurations ofcomputational instances as well as data that can be shared amongst atleast some of the computational instances. For instance, definitions ofcommon security threats that could occur on the computational instances,software packages that are commonly discovered on the computationalinstances, and/or an application store for applications that can bedeployed to the computational instances may reside in a centralinstance. Computational instances may communicate with central instancesby way of well-defined interfaces in order to obtain this data.

In order to support multiple computational instances in an efficientfashion, remote network management platform 320 may implement aplurality of these instances on a single hardware platform. For example,when the aPaaS system is implemented on a server cluster such as servercluster 200, it may operate virtual machines that dedicate varyingamounts of computational, storage, and communication resources toinstances. But full virtualization of server cluster 200 might not benecessary, and other mechanisms may be used to separate instances. Insome examples, each instance may have a dedicated account and one ormore dedicated databases on server cluster 200. Alternatively, acomputational instance such as computational instance 322 may spanmultiple physical devices.

In some cases, a single server cluster of remote network managementplatform 320 may support multiple independent enterprises. Furthermore,as described below, remote network management platform 320 may includemultiple server clusters deployed in geographically diverse data centersin order to facilitate load balancing, redundancy, and/or highavailability.

C. Public Cloud Networks

Public cloud networks 340 may be remote server devices (e.g., aplurality of server clusters such as server cluster 200) that can beused for outsourced computation, data storage, communication, andservice hosting operations. These servers may be virtualized (i.e., theservers may be virtual machines). Examples of public cloud networks 340may include AMAZON WEB SERVICES® and MICROSOFT® AZURE®. Like remotenetwork management platform 320, multiple server clusters supportingpublic cloud networks 340 may be deployed at geographically diverselocations for purposes of load balancing, redundancy, and/or highavailability.

Managed network 300 may use one or more of public cloud networks 340 todeploy applications and services to its clients and customers. Forinstance, if managed network 300 provides online music streamingservices, public cloud networks 340 may store the music files andprovide web interface and streaming capabilities. In this way, theenterprise of managed network 300 does not have to build and maintainits own servers for these operations.

Remote network management platform 320 may include modules thatintegrate with public cloud networks 340 to expose virtual machines andmanaged services therein to managed network 300. The modules may allowusers to request virtual resources, discover allocated resources, andprovide flexible reporting for public cloud networks 340. In order toestablish this functionality, a user from managed network 300 mightfirst establish an account with public cloud networks 340, and request aset of associated resources. Then, the user may enter the accountinformation into the appropriate modules of remote network managementplatform 320. These modules may then automatically discover themanageable resources in the account, and also provide reports related tousage, performance, and billing.

D. Communication Support and Other Operations

Internet 350 may represent a portion of the global Internet. However,Internet 350 may alternatively represent a different type of network,such as a private wide-area or local-area packet-switched network.

FIG. 4 further illustrates the communication environment between managednetwork 300 and computational instance 322, and introduces additionalfeatures and alternative embodiments. In FIG. 4, computational instance322 is replicated across data centers 400A and 400B. These data centersmay be geographically distant from one another, perhaps in differentcities or different countries. Each data center includes supportequipment that facilitates communication with managed network 300, aswell as remote users.

In data center 400A, network traffic to and from external devices flowseither through VPN gateway 402A or firewall 404A. VPN gateway 402A maybe peered with VPN gateway 412 of managed network 300 by way of asecurity protocol such as Internet Protocol Security (IPSEC) orTransport Layer Security (TLS). Firewall 404A may be configured to allowaccess from authorized users, such as user 414 and remote user 416, andto deny access to unauthorized users. By way of firewall 404A, theseusers may access computational instance 322, and possibly othercomputational instances. Load balancer 406A may be used to distributetraffic amongst one or more physical or virtual server devices that hostcomputational instance 322. Load balancer 406A may simplify user accessby hiding the internal configuration of data center 400A, (e.g.,computational instance 322) from client devices. For instance, ifcomputational instance 322 includes multiple physical or virtualcomputing devices that share access to multiple databases, load balancer406A may distribute network traffic and processing tasks across thesecomputing devices and databases so that no one computing device ordatabase is significantly busier than the others. In some embodiments,computational instance 322 may include VPN gateway 402A, firewall 404A,and load balancer 406A.

Data center 400B may include its own versions of the components in datacenter 400A. Thus, VPN gateway 402B, firewall 404B, and load balancer406B may perform the same or similar operations as VPN gateway 402A,firewall 404A, and load balancer 406A, respectively. Further, by way ofreal-time or near-real-time database replication and/or otheroperations, computational instance 322 may exist simultaneously in datacenters 400A and 400B.

Data centers 400A and 400B as shown in FIG. 4 may facilitate redundancyand high availability. In the configuration of FIG. 4, data center 400Ais active and data center 400B is passive. Thus, data center 400A isserving all traffic to and from managed network 300, while the versionof computational instance 322 in data center 400B is being updated innear-real-time. Other configurations, such as one in which both datacenters are active, may be supported.

Should data center 400A fail in some fashion or otherwise becomeunavailable to users, data center 400B can take over as the active datacenter. For example, domain name system (DNS) servers that associate adomain name of computational instance 322 with one or more InternetProtocol (IP) addresses of data center 400A may re-associate the domainname with one or more IP addresses of data center 400B. After thisre-association completes (which may take less than one second or severalseconds), users may access computational instance 322 by way of datacenter 400B.

FIG. 4 also illustrates a possible configuration of managed network 300.As noted above, proxy servers 312 and user 414 may access computationalinstance 322 through firewall 310. Proxy servers 312 may also accessconfiguration items 410. In FIG. 4, configuration items 410 may refer toany or all of client devices 302, server devices 304, routers 306, andvirtual machines 308, any applications or services executing thereon, aswell as relationships between devices, applications, and services. Thus,the term “configuration items” may be shorthand for any physical orvirtual device, or any application or service remotely discoverable ormanaged by computational instance 322, or relationships betweendiscovered devices, applications, and services. Configuration items maybe represented in a configuration management database (CMDB) ofcomputational instance 322.

As noted above, VPN gateway 412 may provide a dedicated VPN to VPNgateway 402A. Such a VPN may be helpful when there is a significantamount of traffic between managed network 300 and computational instance322, or security policies otherwise suggest or require use of a VPNbetween these sites. In some embodiments, any device in managed network300 and/or computational instance 322 that directly communicates via theVPN is assigned a public IP address. Other devices in managed network300 and/or computational instance 322 may be assigned private IPaddresses (e.g., IP addresses selected from the 10.0.0.0-10.255.255.255or 192.168.0.0-192.168.255.255 ranges, represented in shorthand assubnets 10.0.0.0/8 and 192.168.0.0/16, respectively).

IV. Example Device, Application, and Service Discovery

In order for remote network management platform 320 to administer thedevices, applications, and services of managed network 300, remotenetwork management platform 320 may first determine what devices arepresent in managed network 300, the configurations and operationalstatuses of these devices, and the applications and services provided bythe devices, as well as the relationships between discovered devices,applications, and services. As noted above, each device, application,service, and relationship may be referred to as a configuration item.The process of defining configuration items within managed network 300is referred to as discovery, and may be facilitated at least in part byproxy servers 312.

For purposes of the embodiments herein, an “application” may refer toone or more processes, threads, programs, client modules, servermodules, or any other software that executes on a device or group ofdevices. A “service” may refer to a high-level capability provided bymultiple applications executing on one or more devices working inconjunction with one another. For example, a high-level web service mayinvolve multiple web application server threads executing on one deviceand accessing information from a database application that executes onanother device.

FIG. 5A provides a logical depiction of how configuration items can bediscovered, as well as how information related to discoveredconfiguration items can be stored. For sake of simplicity, remotenetwork management platform 320, public cloud networks 340, and Internet350 are not shown.

In FIG. 5A, CMDB 500 and task list 502 are stored within computationalinstance 322. Computational instance 322 may transmit discovery commandsto proxy servers 312. In response, proxy servers 312 may transmit probesto various devices, applications, and services in managed network 300.These devices, applications, and services may transmit responses toproxy servers 312, and proxy servers 312 may then provide informationregarding discovered configuration items to CMDB 500 for storagetherein. Configuration items stored in CMDB 500 represent theenvironment of managed network 300.

Task list 502 represents a list of activities that proxy servers 312 areto perform on behalf of computational instance 322. As discovery takesplace, task list 502 is populated. Proxy servers 312 repeatedly querytask list 502, obtain the next task therein, and perform this task untiltask list 502 is empty or another stopping condition has been reached.

To facilitate discovery, proxy servers 312 may be configured withinformation regarding one or more subnets in managed network 300 thatare reachable by way of proxy servers 312. For instance, proxy servers312 may be given the IP address range 192.168.0/24 as a subnet. Then,computational instance 322 may store this information in CMDB 500 andplace tasks in task list 502 for discovery of devices at each of theseaddresses.

FIG. 5A also depicts devices, applications, and services in managednetwork 300 as configuration items 504, 506, 508, 510, and 512. As notedabove, these configuration items represent a set of physical and/orvirtual devices (e.g., client devices, server devices, routers, orvirtual machines), applications executing thereon (e.g., web servers,email servers, databases, or storage arrays), relationshipstherebetween, as well as services that involve multiple individualconfiguration items.

Placing the tasks in task list 502 may trigger or otherwise cause proxyservers 312 to begin discovery. Alternatively or additionally, discoverymay be manually triggered or automatically triggered based on triggeringevents (e.g., discovery may automatically begin once per day at aparticular time).

In general, discovery may proceed in four logical phases: scanning,classification, identification, and exploration. Each phase of discoveryinvolves various types of probe messages being transmitted by proxyservers 312 to one or more devices in managed network 300. The responsesto these probes may be received and processed by proxy servers 312, andrepresentations thereof may be transmitted to CMDB 500. Thus, each phasecan result in more configuration items being discovered and stored inCMDB 500.

In the scanning phase, proxy servers 312 may probe each IP address inthe specified range of IP addresses for open Transmission ControlProtocol (TCP) and/or User Datagram Protocol (UDP) ports to determinethe general type of device. The presence of such open ports at an IPaddress may indicate that a particular application is operating on thedevice that is assigned the IP address, which in turn may identify theoperating system used by the device. For example, if TCP port 135 isopen, then the device is likely executing a WINDOWS® operating system.Similarly, if TCP port 22 is open, then the device is likely executing aUNIX® operating system, such as LINUX®. If UDP port 161 is open, thenthe device may be able to be further identified through the SimpleNetwork Management Protocol (SNMP). Other possibilities exist. Once thepresence of a device at a particular IP address and its open ports havebeen discovered, these configuration items are saved in CMDB 500.

In the classification phase, proxy servers 312 may further probe eachdiscovered device to determine the version of its operating system. Theprobes used for a particular device are based on information gatheredabout the devices during the scanning phase. For example, if a device isfound with TCP port 22 open, a set of UNIX®-specific probes may be used.Likewise, if a device is found with TCP port 135 open, a set ofWINDOWS®-specific probes may be used. For either case, an appropriateset of tasks may be placed in task list 502 for proxy servers 312 tocarry out. These tasks may result in proxy servers 312 logging on, orotherwise accessing information from the particular device. Forinstance, if TCP port 22 is open, proxy servers 312 may be instructed toinitiate a Secure Shell (SSH) connection to the particular device andobtain information about the operating system thereon from particularlocations in the file system. Based on this information, the operatingsystem may be determined. As an example, a UNIX® device with TCP port 22open may be classified as AIX®, HPUX, LINUX®, MACOS®, or SOLARIS®. Thisclassification information may be stored as one or more configurationitems in CMDB 500.

In the identification phase, proxy servers 312 may determine specificdetails about a classified device. The probes used during this phase maybe based on information gathered about the particular devices during theclassification phase. For example, if a device was classified as LINUX®,a set of LINUX®-specific probes may be used. Likewise, if a device wasclassified as WINDOWS® 2012, as a set of WINDOWS®-2012-specific probesmay be used. As was the case for the classification phase, anappropriate set of tasks may be placed in task list 502 for proxyservers 312 to carry out. These tasks may result in proxy servers 312reading information from the particular device, such as basicinput/output system (BIOS) information, serial numbers, networkinterface information, media access control address(es) assigned tothese network interface(s), IP address(es) used by the particular deviceand so on. This identification information may be stored as one or moreconfiguration items in CMDB 500.

In the exploration phase, proxy servers 312 may determine furtherdetails about the operational state of a classified device. The probesused during this phase may be based on information gathered about theparticular devices during the classification phase and/or theidentification phase. Again, an appropriate set of tasks may be placedin task list 502 for proxy servers 312 to carry out. These tasks mayresult in proxy servers 312 reading additional information from theparticular device, such as processor information, memory information,lists of running processes (applications), and so on. Once more, thediscovered information may be stored as one or more configuration itemsin CMDB 500.

Running discovery on a network device, such as a router, may utilizeSNMP. Instead of or in addition to determining a list of runningprocesses or other application-related information, discovery maydetermine additional subnets known to the router and the operationalstate of the router's network interfaces (e.g., active, inactive, queuelength, number of packets dropped, etc.). The IP addresses of theadditional subnets may be candidates for further discovery procedures.Thus, discovery may progress iteratively or recursively.

Once discovery completes, a snapshot representation of each discovereddevice, application, and service is available in CMDB 500. For example,after discovery, operating system version, hardware configuration, andnetwork configuration details for client devices, server devices, androuters in managed network 300, as well as applications executingthereon, may be stored. This collected information may be presented to auser in various ways to allow the user to view the hardware compositionand operational status of devices, as well as the characteristics ofservices that span multiple devices and applications.

Furthermore, CMDB 500 may include entries regarding dependencies andrelationships between configuration items. More specifically, anapplication that is executing on a particular server device, as well asthe services that rely on this application, may be represented as suchin CMDB 500. For example, suppose that a database application isexecuting on a server device, and that this database application is usedby a new employee onboarding service as well as a payroll service. Thus,if the server device is taken out of operation for maintenance, it isclear that the employee onboarding service and payroll service will beimpacted. Likewise, the dependencies and relationships betweenconfiguration items may be able to represent the services impacted whena particular router fails.

In general, dependencies and relationships between configuration itemsmay be displayed on a web-based interface and represented in ahierarchical fashion. Thus, adding, changing, or removing suchdependencies and relationships may be accomplished by way of thisinterface.

Furthermore, users from managed network 300 may develop workflows thatallow certain coordinated activities to take place across multiplediscovered devices. For instance, an IT workflow might allow the user tochange the common administrator password to all discovered LINUX®devices in a single operation.

In order for discovery to take place in the manner described above,proxy servers 312, CMDB 500, and/or one or more credential stores may beconfigured with credentials for one or more of the devices to bediscovered. Credentials may include any type of information needed inorder to access the devices. These may include userid/password pairs,certificates, and so on. In some embodiments, these credentials may bestored in encrypted fields of CMDB 500. Proxy servers 312 may containthe decryption key for the credentials so that proxy servers 312 can usethese credentials to log on to or otherwise access devices beingdiscovered.

The discovery process is depicted as a flow chart in FIG. 5B. At block520, the task list in the computational instance is populated, forinstance, with a range of IP addresses. At block 522, the scanning phasetakes place. Thus, the proxy servers probe the IP addresses for devicesusing these IP addresses, and attempt to determine the operating systemsthat are executing on these devices. At block 524, the classificationphase takes place. The proxy servers attempt to determine the operatingsystem version of the discovered devices. At block 526, theidentification phase takes place. The proxy servers attempt to determinethe hardware and/or software configuration of the discovered devices. Atblock 528, the exploration phase takes place. The proxy servers attemptto determine the operational state and applications executing on thediscovered devices. At block 530, further editing of the configurationitems representing the discovered devices and applications may takeplace. This editing may be automated and/or manual in nature.

The blocks represented in FIG. 5B are examples. Discovery may be ahighly configurable procedure that can have more or fewer phases, andthe operations of each phase may vary. In some cases, one or more phasesmay be customized, or may otherwise deviate from the exemplarydescriptions above.

In this manner, a remote network management platform may discover andinventory the hardware, software, and services deployed on and providedby the managed network. As noted above, this data may be stored in aCMDB of the associated computational instance as configuration items.For example, individual hardware components (e.g., computing devices,virtual servers, databases, routers, etc.) may be represented ashardware configuration items, while the applications installed and/orexecuting thereon may be represented as software configuration items.

The relationship between a software configuration item installed orexecuting on a hardware configuration item may take various forms, suchas “is hosted on”, “runs on”, or “depends on”. Thus, a databaseapplication installed on a server device may have the relationship “ishosted on” with the server device to indicate that the databaseapplication is hosted on the server device. In some embodiments, theserver device may have a reciprocal relationship of “used by” with thedatabase application to indicate that the server device is used by thedatabase application. These relationships may be automatically foundusing the discovery procedures described above, though it is possible tomanually set relationships as well.

The relationship between a service and one or more softwareconfiguration items may also take various forms. As an example, a webservice may include a web server software configuration item and adatabase application software configuration item, each installed ondifferent hardware configuration items. The web service may have a“depends on” relationship with both of these software configurationitems, while the software configuration items have a “used by”reciprocal relationship with the web service. Services might not be ableto be fully determined by discovery procedures, and instead may rely onservice mapping (e.g., probing configuration files and/or carrying outnetwork traffic analysis to determine service level relationshipsbetween configuration items) and possibly some extent of manualconfiguration.

Regardless of how relationship information is obtained, it can bevaluable for the operation of a managed network. Notably, IT personnelcan quickly determine where certain software applications are deployed,and what configuration items make up a service. This allows for rapidpinpointing of root causes of service outages or degradation. Forexample, if two different services are suffering from slow responsetimes, the CMDB can be queried (perhaps among other activities) todetermine that the root cause is a database application that is used byboth services having high processor utilization. Thus, IT personnel canaddress the database application rather than waste time considering thehealth and performance of other configuration items that make up theservices.

V. Example Infrastructure Remediation Tools

As discussed above, computational instance 322 could put into operationa dual-database system to reduce database query delays. Such a systemmay contain a first database engine and a second database engine. Thefirst database engine could be an authoritative database for thedual-database system. The second database engine could be a read-onlyreplica of the first database engine and could be configured with atechnology that allows for efficient querying. During operations, arouting engine could receive database queries directed to thedual-database system and appropriately route the queries to either thefirst database engine or the second database engine.

Sometimes, however, the dual-database system could experienceperformance issues that cause it to perform sub-optimally or behave inan unintended way. Upon discovering a performance issue, a user couldsubmit a support ticket and an agent may be assigned to troubleshoot theperformance issue raised by the ticket. During the troubleshootingprocess, the assigned agent may examine portions of the dual-databasesystem in an attempt to identify components of the dual-database systemthat encompass the performance issue. Yet, if the assigned agent is nototherwise familiar with aspects of the dual-database system, thistroubleshooting process can become overly complex and time consuming.Further, even after identifying the components that encompass theperformance issue, formulating an appropriate response to get thedual-database system fully restored may take days or even weeks, as theagent may have limited resources with which to resolve the performanceissue.

To address this and other issues, remote network management platform 320may include an infrastructure remediation tool that can pinpoint andautomatically resolve performance issues in a dual-database system. Theinfrastructure remediation tool could take the form of a backgroundprocess, an executable application, or the like. The disclosedinfrastructure remediation tool could locate and resolve performanceissues within dual-database systems operating in various computationalinstances within remote network management platform 320. For example,the infrastructure remediation tool could pinpoint and automaticallyresolve performance issues in dual-database systems operating incomputational instance 322, 324, and/or 326. For simplicity, exampleswill now be described using computational instance 322. However, thedisclosed principles could apply in other scenarios with othercomputational instances as well.

FIG. 6 depicts network architecture 600, in accordance with exampleembodiments. Network architecture 600 includes two main components,managed network 300 and computational instance 322, which may becommunicatively connected by way of a network, such as Internet 350.

Herein, the term “performance issues” is to be interpreted broadlyunless context suggests otherwise. Thus, performance issues may relateto the availability, correctness, throughput, latency, or any otherrelevant aspect of any component of a dual-database system.

Further, unless context suggests otherwise, a “performance issue” is notsolely limited to a single aspect or component of a dual-databasesystem. For example, in some cases, a performance issue could encompassmultiple aspects or components of the dual-database system. When viewedindividually, each of these multiple aspects or component may beobserved to be functioning normally. However, when viewed in aggregate,the multiple aspects or components could suggest a composite performanceissue within the dual-database system.

As noted above, managed network 300 may be an enterprise network used byan entity for computing and communication tasks, as well as storage ofdata. In examples, managed network 300 may utilize one or more databaseengines contained within computational instance 322.

Users 602 and users 604 can represent people or sources (e.g., anotherenterprise) that use the database engines provided by computationalinstance 322. In example embodiments, users 602 may represent peoplethat work for the entity associated with managed network 300, such asengineers, scientists, managers, accountants, financial analysts, ITstaff, and so on, whereas users 604 may correspond to people outside ofthe entity associated with managed network 300.

Computational instance 322 may be disposed within remote networkmanagement platform 320 and may be dedicated to managed network 300.Computational instance 322 may store discovered configuration items thatrepresent the environment of managed network 300. Computational instance322 could include dual-database system 610, which may take the form of aseries of interconnected server devices (e.g., a plurality of serverclusters such as server cluster 200) that can be used for computation,data storage, communication, and other operations. In some embodiments,some or all of the devices of dual-database system 610 may be disposedin a remote network, such as public cloud networks 340, and may becommunicatively connected to computational instance 322.

In line with the discussion above, dual-database system 610 may be adatabase system designed to reduce database query delays. As show inFIG. 6, dual-database system 610 may contain master database engine 612,replicated database engine 614, routing engine 616, replication engine618, and infrastructure remediation tool 620. However, in otherimplementations, dual-database system 610 could include a fewer numberof components, a greater number of components, or other types ofcomponents.

Master database engine 612 could be an authoritative database of enginedual-database system 610. That is, master database engine 612 may act asa single source of truth for data within dual-database system 610. As anexample, if another database engine in dual-database system 610contained information that conflicted with information in masterdatabase engine 612, computational instance 322 would use theinformation in master database engine 612 rather than the other databaseengine. During operations, users 602 and/or 604 could query data frommaster database engine 612 and write data to master database engine 612.In example embodiments, master database engine 612 may take the form ofa row-oriented database engine, such as MARIADB®, AMAZON® AURORA®,and/or another row-oriented database engine. Further, in someembodiments, master database engine 612 could take the form of CMDB 500.

Replicated database engine 614 could be a replica of master databaseengine 612. That is, replicated database engine 614 may contain copiesof at least some of the records in master database engine 612. Duringoperations, users 602 and/or 604 could query data from replicateddatabase engine 614 but may be prevented from writing data to replicateddatabase engine 614. In example embodiments, replicated database engine614 could be configured with a technology that allows for efficientquerying. For example, replicated database engine 614 could take theform of a column-oriented database engine, such as MONETDB®, AMAZON®REDSHIFT®, and/or another column-oriented database engine.

In some embodiments, master database engine 612 may be an SQL-baseddatabase and replicated database engine 614 may be a NoSQL-baseddatabase. The former uses tables and exhibits lower-latency writes buthigher-latency reads. The latter generally uses some form of flat filesand exhibits lower-latency reads but higher-latency writes.

Routing engine 616 may be configured to receive database queriesdirected toward dual-database system 610 and appropriately route thosedatabase queries to either master database engine 612 or replicateddatabase engine 614. Routing engine 616 could use various routing rulesto determine which database engine to assign an incoming query. Suchrouting rules may organize incoming queries based on various criteria.As one example, routing engine 616 may consider the origination point ofa database query when deciding where to route the query. For instance,if the database query originates from a web application—which typicallyrequire a fast response time—then routing engine 616 may route the queryto replicated database engine 614. On the other hand, if the queryoriginates from a financial auditing tool—which typically requireauthoritative data—then routing engine 616 may route the query to masterdatabase engine 612. As another example, routing engine 616 may factorthe customer or employee status of the user submitting the databasequery. For instance, if a database query originates from a user with avery important person (VIP) status, then routing engine 616 may routethe query to replicated database engine 614. Notably, replicateddatabase engine 614 may use other types of routing rules when decidingwhere to route an incoming database query.

Replication engine 618 may be configured to replicate data from masterdatabase engine 612 to replicated database engine 614. To do this,replication engine 618 may perform various types of replicationprocesses. For example, if a record is in master database engine 612 butnot in replicated database engine 614, replication engine 618 mayperform a replication process that involves inserting that record intoreplicated database engine 614. As another example, if replicateddatabase engine 614 contains a particular record and master databaseengine 612 contains an updated version of that particular record,replication engine 618 may perform a replication process that involvesdeleting the particular record from replicated database engine 614 andthen inserting the updated version of that particular record intoreplicated database engine 614.

In some embodiments, as a result of the replication processes performedby replication engine 618, the data in replicated database engine 614could become fragmented. That is, related pieces of data in replicateddatabase engine 614 may be broken up into non-contiguous data blocksthat are stored at various locations in memory. To resolve this issue,replication engine 618 may also contain a data defragmentation componentthat performs a defragmentation process (e.g., a maintenance process) torearrange the data stored in replicated database engine 614 so thatrelated pieces of data are stored as contiguous data blocks in memory.

In line with the discussion above, occasionally, dual-database system610 may experience a performance issue that causes it to performsub-optimally or produce unexpected results. Upon discovering aperformance issue, users 602 and/or 604 could submit a support ticket.An agent may be assigned to resolve the performance issue raised in theticket, and may use the services of infrastructure remediation tool 620in doing so. This agent may be an IT staff member, a software engineer,a customer service engineer, or some other entity.

As noted, infrastructure remediation tool 620 could be configured topinpoint a set of performance issues in dual-database system 610. Afteridentifying the set of performance issues, infrastructure remediationtool 620 could execute various subroutines to resolve those performanceissues. If infrastructure remediation tool 620 cannot execute asubroutine (or if no subroutines exist for a particular performanceissue), infrastructure remediation tool 620 could display the set ofperformance issues in a logical manner, perhaps on a graphical userinterface. The agent could then use the graphical user interface tolocate components in dual-database system 610 that may need to bemanually readjusted.

To facilitate its operations, infrastructure remediation tool 620 mayreceive operational data from various components in dual-database system610. For example, infrastructure remediation tool 620 may receiveoperational data from master database engine 612, replicated databaseengine 614, routing engine 616, replication engine 618, adefragmentation engine disposed within replication engine 618, and soon. As used herein, operational data is any data that relates to theoperations of a particular component. In example embodiments,operational data from master database engine 612 may include dataindicating when records were added, deleted, or updated, timestampsindicating when maintenance (e.g., defragmentation) has been performedon master database engine 612, and so on. Operational data fromreplicated database engine 614 may include timestamps indicating whenmaintenance has been performed on replicated database engine 614,timestamps indicating when seeding (i.e., a process in which an initialset of records are provided to a database engine) has occurred onreplicated database engine 614, timestamps indicating when replicateddatabase engine 614 became or was available to accept incoming queries,and so on. Operational data from routing engine 616 may include dataindicating the volume of incoming queries over a period of time, therouting decisions for various queries, and so on. Operational data fromreplication engine 618 may include timestamps indicating when areplication process has been performed by replication engine 618, dataon the lag of the replication process, and so on. Operational data fromthe defragmentation engine disposed within replication engine 618 mayinclude timestamps indicating when a defragmentation process has beenperformed by the defragmentation engine, data on the lag of thedefragmentation process, and so on. Notably, other examples ofoperational data may exist and are contemplated in the disclosureherein.

In example embodiments, a component may provide operational data toinfrastructure remediation tool 620 in response to a trigger. Three maintypes of triggers may be supported. Record-based triggers may causecomponents to provide operational data when a change to one or morespecific database records (e.g., one or more records in master databaseengine 612 and/or replicated database engine 614) occurs. These changesmay include the creation of a record, the updating of a record, and thedeletion of a record. Scheduled triggers may cause components to provideoperational data at one or more specified times. Such a schedule maytrigger a component to transmit operational data every second, every fewminutes, daily, weekly, monthly, just once (at a specified time), or ata user-specified interval. Event-based triggers may cause components toprovide operational data when an event occurs on dual-database system610. For example, event-based triggers may be based on events occurringwithin replication engine 618 (e.g., the initiation of a replicationprocess), events occurring within routing engine 616 (e.g., routingengine 616 routing a request to either replicated database engine 614 ormaster database engine 612), and perhaps other types of events. Othertypes of triggers could also be supported.

In line with the discussion above, infrastructure remediation tool 620may enable the specification of various types of performance issueindicators based on the received operational data. A performance issueindicator, as used herein, is a specific series of logical conditionsthat, when satisfied by the operational data, cause the performanceissue indicator to be “active.” In some embodiments, performance issueindicators are configured through use of a software-based design tool.The tool could allow an indicator designer to define conditions,triggers, actions, input data, and other characteristics of theindicators. The design tool may utilize a GUI, and may be embodied as aseries of one or more web pages and/or web-based applications deployedupon computational instance 322. In other embodiments, performance issueindicators can be configured programmatically. For example, the userfrom remote network management platform 320 could configure aperformance issue indicator by modifying the source code or aconfiguration file of infrastructure remediation tool 620.

FIG. 7 illustrates elements of a performance issue indicator, accordingto example embodiments. As shown, performance issue indicator 700includes two separate conditions, condition 710 and condition 720, thatare joined by a logical OR. This means that either condition 710 orcondition 720 must be satisfied in order for performance issue indicator700 to be considered as “active.” As used herein, a condition may be alogical expression that compares an input metric to a criteria. If thelogical expression holds true, then the condition is deemed assatisfied. A performance issue indicator may have multiple conditions,each of which can be joined together using logical ANDs/ORs.

As illustrated in FIG. 7, condition 710 includes three elements: inputmetric 712, operator 714, and criteria 716.

Input metric 712 could be a metric that is calculated based onoperational data from dual-database system 610. In some examples, inputmetric 712 is a metric calculated from a single component. For instance,input metric 712 could be calculated just based on operational datareceived from replicated database engine 614. In other examples, inputmetric 712 may be a metric that is calculated based on operational datafrom multiple components. For instance, input metric 712 could becalculated based on operational data received from replication engine618 and from routing engine 616. In the example illustrated in FIG. 7,input metric 712 is a variable named “seeding”, which is a metric thatcaptures whether replicated database engine 614 is performing a seedingoperation.

Operator 714 is used to compare input metric 712 to criteria 716. If thecomparison specified by operator 714 holds true, then condition 710 maybe deemed as satisfied. In the example illustrated in FIG. 7, operator714 takes the form of an “equal to” operator. However, other types ofoperators may be used, including “equal or greater than”, “greaterthan”, “greater than or equal to”, “less than”, and “less than or equalto”, and so on.

Criteria 716 may be a user defined input that is compared against inputmetric 712. Criteria 716 may take the form of a Boolean value, anumerical value, a formulaic expression, a metric that representsoperational data from dual-database system 610, or possibly anotherform. In the example illustrated in FIG. 7, criteria 716 takes the formof the Boolean value “TRUE”.

FIG. 8 depicts a table containing various performance issue indicators,in accordance with example embodiments. As discussed above, theindicators in table 800 may be specified by a user from remote networkmanagement platform 320. This may be accomplished, for example, by a GUIprovided by computational instance 322 to a user from remote networkmanagement platform 320 or may be accomplished programmatically.Infrastructure remediation tool 620 may monitor the indicators specifiedin table 800 to determine whether the conditions for the indicators aresatisfied by operational data received from dual-database system 610. Ifthe conditions for an indicator are satisfied, infrastructureremediation tool 620 may consider that indicator as being “active.”

As shown, each performance issue indicator in table 800 includes entriesfor three columns: (i) indicator ID column, which provides a uniqueidentifier for the indicator, (ii) conditions column, which outlines theconditions for the indicator, and (iii) status column, which indicateswhether the conditions for the indicator are satisfied by operationaldata received by infrastructure remediation tool 620 from dual-databasesystem 610.

Indicator 810 may be a performance issue indicator that indicateswhether replicated database engine 614 has been seeding for more than 3hours. Accordingly, the operational data for indicator 810 (i.e., theinput metric ‘seeding” and the input metric “persisting”) may originatefrom replicated database engine 614. If replicated database engine 614has been persisting for more than 3 hours and is in a seeding state,then the conditions for indicator 810 may be satisfied and the statuscolumn for indicator 810 may be “active.” Otherwise, if replicateddatabase engine 614 has not been persisting for more than 3 hours or isnot in a seeding state, then the conditions for indicator 810 may not besatisfied and the status column for indicator 810 may be “inactive.” Inthe example shown in FIG. 8, the status column for indicator 810 is“inactive,” meaning that replicated database engine 614 has not beenseeding for more than 3 hours.

Indicator 820 may be a performance issue indicator that indicateswhether replicated database engine 614 has been undergoing a maintenanceprocess (e.g., a defragmentation process) for more than 1 hour.Accordingly, the operational data for indicator 820 (i.e., the inputmetric ‘maintenance” and the input metric “persisting”) may originatefrom replicated database engine 614 as well as replication engine 618.If replicated database engine 614 has been persisting for more than 1hour and is in a maintenance state, then the conditions for indicator820 may be satisfied and the status column for indicator 820 may be“active.” Otherwise, if replicated database engine 614 has not beenpersisting for more than 1 hour or is not in a maintenance state, thenthe conditions for indicator 820 may not be satisfied and the statuscolumn for indicator 820 may be “inactive.” In the example shown in FIG.8, the status for indicator 820 is “active,” meaning that replicateddatabase engine 614 has been undergoing a maintenance process for morethan 1 hour.

Indicator 830 may be a performance issue indicator that indicateswhether replicated database engine 614 has been operating for more than6 hours without being shut down. Accordingly, the operational data forindicator 830 (i.e., the input metric “replicatedDB uptime”) mayoriginate from replicated database engine 614. If the uptime ofreplicated database engine 614 is greater than 6 hours, then thecondition for indicator 830 may be satisfied and the status column forindicator 830 may be “active.” Otherwise, if the uptime of replicateddatabase engine 614 is not greater than 6 hours, then the condition forindicator 830 may not be satisfied and the status column for indicator830 may be “inactive.” In the example shown in FIG. 8, the status forindicator 830 is “active,” meaning that replicated database engine 830has operating for more than 6 hours without being shut down.

Indicator 840 may be a performance issue indicator that indicateswhether replicated database engine 614 is able to accept incomingdatabase queries and whether replicated database engine 614 is undermaintenance. Accordingly, the operational data for indicator 840 (i.e.,the input metric “alive” and the input metric “maintenance”) mayoriginate from replicated database engine 614. If replicated databaseengine 614 is not alive and is not in a maintenance state, then theconditions for indicator 840 may be satisfied and the status column forindicator 840 may be “active.” Otherwise, if replicated database engine614 is alive or is in a maintenance state, then the conditions forindicator 840 may not be satisfied and the status column for indicator840 may be “inactive.” In the example shown in FIG. 8, the status forindicator 840 is “active,” meaning that replicated database engine 614is unable to accept incoming database queries, even though it is notundergoing maintenance.

Indicator 850 may be a performance issue indicator that indicateswhether the credentials to access replicated database engine 614 arefaulty. Accordingly, the operational data for indicator 850 (i.e., theinput metric “ReplicatedDB_Crediential_is_Faulty”) may originate fromreplicated database engine 614. If the credentials to access replicateddatabase engine 614 are faulty, then the condition for indicator 850 maybe satisfied and the status column for indicator 850 may be “active.”Otherwise, if the credentials to access replicated database engine 614are not faulty, then the condition for indicator 850 may not besatisfied and the status column for indicator 850 may be “inactive.” Inthe example shown in FIG. 8, the status for indicator 850 is “active,”meaning the credentials to access replicated database engine 614 arefaulty.

In some embodiments, the operational data provided to infrastructureremediation tool 620 may originate from infrastructure remediation tool620 itself. For instance, indicator 860 may be a performance issueindicator that indicates whether the disk utilization of infrastructureremediation tool 620 is at or over 90%. Accordingly, the operationaldata for indicator 860 (i.e., the input metric “disk_utilization”) mayoriginate from random access memory (RAM) disposed within infrastructureremediation tool 620. If the disk utilization of infrastructureremediation tool 620 is at or over 90%, then the condition for indicator860 may be satisfied and the status column for indicator 860 may be“active.” Otherwise, if the disk utilization of infrastructureremediation tool 620 is under 90%, then the condition for indicator 860may not be satisfied and the status column for indicator 860 may be“inactive.” In the example shown in FIG. 8, the status for indicator 860is “active,” meaning the disk utilization of infrastructure remediationtool 620 is at or over 90%. Due to this high disk utilization,infrastructure remediation tool 620 may be unable to cache, andtherefore unable to evaluate, newer operational data.

Indicator 870 may be a performance issue indicator that indicateswhether a maintenance process has been performed on replicated databaseengine 614 within the past 20 minutes (e.g., as determined bytimestamps) and whether the lag of a replication process performed byreplication engine 618 is greater than 5 minutes. Accordingly, theoperational data for indicator 870 (i.e., the input metric“time_since_last_maintenance” and the input metric “replication lag”)may originate from replicated database engine 614 as well as replicationengine 618. If a maintenance process has not been performed onreplicated database engine 614 within the past 20 minutes and the lag ofa replication process performed by replication engine 618 is greaterthan 5 minutes, then the condition for indicator 870 may be satisfiedand the status column for indicator 870 may be “active.” Otherwise, if amaintenance process has been performed on replicated database engine 614within the past 20 minutes or if the lag of a replication processperformed by replication engine 618 is not greater than 5 minutes, thenthe condition for indicator 870 may not be satisfied and the statuscolumn for indicator 870 may be “inactive.” In the example shown in FIG.8, the status for indicator 870 is “active,” meaning that a maintenanceprocess has not been performed on replicated database engine 614 withinthe past 20 minutes and the lag of a replication process performed byreplication engine 618 is greater than 5 minutes.

Indicator 880 may be a performance issue indicator that indicateswhether a maintenance process has been performed on replicated databaseengine 614 within the last 6 hours.

Accordingly, the operational data for indicator 880 (i.e., the inputmetric “time_since_last_maintenance”) may originate from replicateddatabase engine 614 as well as replication engine 618. If a maintenanceprocess has not been performed on replicated database engine 614 withinthe last 6 hours, then the condition for indicator 880 may be satisfiedand the status column for indicator 880 may be “active.” Otherwise, if amaintenance process has been performed on replicated database engine 614within the last 6 hours, then the condition for indicator 880 may not besatisfied and the status column for indicator 880 may be “inactive.” Inthe example shown in FIG. 8, the status for indicator 880 is “active,”meaning a maintenance process has not been performed on replicateddatabase engine 614 within the last 6 hours.

Indicator 890 may be a performance issue indicator that indicateswhether a replication process has been performed by replication engine618 within the last 3 hours. Accordingly, the operational data forindicator 890 (i.e., the input metric “time_since_last_replication”) mayoriginate from replicated database engine 614 as well as replicationengine 618. If a replication process has not been performed byreplication engine 618 within the last 3 hours, then the condition forindicator 890 may be satisfied and the status column for indicator 890may be “active.” Otherwise, if a replication process has been performedby replication engine 618 within the last 3 hours, then the conditionfor indicator 890 may not be satisfied and the status column forindicator 890 may be “inactive.” In the example shown in FIG. 8, thestatus for indicator 890 is “active,” meaning a replication process hasnot been performed by replication engine 618 within the last 3 hours.

Notably, the indicators presented in FIG. 8 are used for the purpose ofexample and are not intended to be limiting with respect to theembodiments herein. In practice, table 800 could include a fewer numberof indicators or a greater number of indicators, perhaps even hundredsor thousands. Further, other types of indicators are also possible andare contemplated in the disclosure herein.

FIG. 9 depicts a table containing mappings between performance issueindicators and subroutines, in accordance with example embodiments. Asdiscussed above, the subroutines and the mappings in table 900 may bespecified by a user from remote network management platform 320. Thismay be accomplished, for example, by a GUI provided by computationalinstance 322 to the user from remote network management platform 320 ormay be accomplished programmatically. Infrastructure remediation tool620 may monitor the performance issue indicators in table 800 todetermine whether a performance issue indicator becomes “active.” If aperformance issue indicator becomes active and has an associated mappingin table 900, then infrastructure remediation tool 620 may execute thesubroutine specified by the mapping. Otherwise, infrastructureremediation tool 620 may escalate the performance issue to an agent.

As shown, each mapping in table 900 includes entries for two columns:(i) indicator ID column, which contains unique identifiers correspondingto performance issues, and (ii) a subroutine column, which designates afilename (e.g., a pathname) for an executable subroutine. In exampleembodiments, a subroutine may take the form of object code, machinecode, executable instructions, build instructions, configurationinstructions, or the like.

Entry 930 is a mapping between indicator 830 and the subroutine“defrag.sh”. This means that when indicator 830 becomes “active” (e.g.,all the conditions for indicator 830 are satisfied), infrastructureremediation tool 620 will execute the subroutine “defrag.sh”. In exampleembodiments, executing “defrag.sh” could initiate a defragmentationprocess on replicated database engine 614.

Entry 940 is a mapping between indicator 840 and the subroutine“test_query.java”. This means that when indicator 840 becomes “active”(e.g., all the conditions for indicator 840 are satisfied),infrastructure remediation tool 620 will execute the subroutine“test_query.java”. In example embodiments, executing “test queryjava”could run a test database query on replicated database engine 614 toconfirm that replicated database engine 614 is healthy. If the testquery returns a response, “test_query.java” could then change the inputmetric “alive” for replicated database engine 614 to “TRUE”.

Entry 950 is a mapping between indicator 850 and the subroutine“correct_credentials.java”. This means that when indicator 850 becomes“active” (e.g., all the conditions for indicator 850 are satisfied),infrastructure remediation tool 620 will execute the subroutine“correct_credentials.java”. In example embodiments, executing“correct_credentials.java” could reset the authentication credentialsfor replicated database engine 614.

Entry 960 is a mapping between indicator 860 and the subroutine“flush_records.java”. This means that when indicator 860 becomes“active” (e.g., all the conditions for indicator 860 are satisfied),infrastructure remediation tool 620 will execute the subroutine“flush_records.java”. In example embodiments, executing“flush_records.java” could flush all operational data cached withininfrastructure remediation tool 620 that have timestamps more than a dayold, a week old, a month old, and so on.

Entry 970 is a mapping between indicator 870 and the subroutine“reset_replication_process.sh”. This means that when indicator 870becomes “active” (e.g., all the conditions for indicator 870 aresatisfied), infrastructure remediation tool 620 will execute thesubroutine “reset_replication_process.sh”. In example embodiments,executing “reset_replication_process.sh” could reset a replicationprocess being performed by replication engine 618, for example, byterminating and then restarting the replication process, modifying thefrequency of the replication process, modifying the types of recordsthat are to be replicated during the replication process, and so on.

Entry 980 is a mapping between indicator 880 and the subroutine“reset_maintenance_process.sh”. This means that when indicator 880becomes “active” (e.g., all the conditions for indicator 880 aresatisfied), infrastructure remediation tool 620 will execute thesubroutine “reset_maintenance_process.sh”. In example embodiments,executing “reset_maintenance_process.sh” could reset a defragmentationprocess being performed by replication engine 618, for example, byterminating and then restarting the defragmentation process, modifyingthe frequency of the defragmentation process, modifying the types ofrecords that are to be defragmented during the defragmentation process,and so on.

A remediation subroutine could be included as part of multiple mappingsin mappings 900. For example, entry 990 includes a mapping betweenindicator 890 and the previously described subroutine“reset_replication_process.sh”. This means that when indicator 890becomes “active” (e.g., all the conditions for indicator 890 aresatisfied), infrastructure remediation tool 620 will execute thesubroutine “reset_replication_process.sh”.

Further, an indicator could be included as part of multiple mappings inmappings 900. For example, entry 992 includes a mapping betweenindicator 890 and the remediation subroutine “restart_replicated_db.sh.”This means that when indicator 890 becomes “active” (e.g., all theconditions for indicator 890 are satisfied), infrastructure remediationtool 620 could, in addition to executing the subroutine“reset_replication_process.sh,” execute the subroutine“restart_replicated_db.sh.” In example embodiments, executing“restart_replicated_db.sh” could restart_replicated database engine 614.

In some embodiments, infrastructure remediation tool 620 executesremediation subroutines in parallel. For example, when indicator 890becomes “active,” infrastructure remediation tool 620 couldsimultaneously execute the subroutines “reset_replication_process.sh”and “restart_replicated_db.sh.” In other embodiments, infrastructureremediation tool 620 executes remediation subroutines sequentially. Forinstance, when indicator 890 becomes “active,” infrastructureremediation tool 620 could execute “reset_replication_process.sh” andthen determine whether “reset_replication_process.sh” succeeded inresolving the performance issue raised by indicator 890. If“reset_replication_process.sh” did not succeed, then infrastructureremediation tool 620 could execute “restart_replicated_db.sh.”

In example embodiments, infrastructure remediation tool 620 maydetermine the success rates of various remediation subroutines and mayupdate mappings 900 based on those determined success rates. Forinstance, if infrastructure remediation tool 620 determines that aremediation subroutine has a threshold low success rate (e.g., did notremediate a performance issue a threshold number of times, did notremediate a performance issue a threshold percentage of times, etc.),then infrastructure remediation tool 620 could remove from mappings 900all mappings in between that remediation subroutine and indicators thatwere unsuccessfully resolved by that remediation subroutine. On theother hand, if infrastructure remediation tool 620 determines that aremediation subroutine has a threshold high success rate (e.g.,successfully remediated a performance issue a threshold number of times,successfully remediated a performance issue a threshold percentage oftimes, etc.), then infrastructure remediation tool 620 could add tomappings 900 mappings between that remediation subroutine and indicatorsthat were successfully resolved by that remediation subroutine. Further,if infrastructure remediation tool 620 determines that remediationsubroutine SUB_A has higher success rate than remediation subroutineSUB_B in resolving a particular indicator, then infrastructureremediation tool 620 could set remediation subroutine SUB_A as the firstsubroutine to be executed when that particular indicator becomes“active.”

Mappings 900 do not contain entries for indicator 810 or indicator 820.This means that indicator 810 or indicator 820 do not have associatedsubroutines. Accordingly, if either indicator 810 or indicator 820became “active,” infrastructure remediation tool 620 would immediatelyescalate indicator 810 and indicator 820 to an agent rather than firstperforming an automated response.

Notably, the mappings presented in FIG. 9 are used for the purpose ofexample and are not intended to be limiting with respect to theembodiments herein. In practice, table 900 could include a fewer numberof mappings or a greater number of mappings, perhaps even hundreds orthousands. Further, other types of mappings are also possible and arecontemplated in the disclosure herein.

Example operations of infrastructure remediation tool 620 are depictedas flow chart 1010 in FIG. 10. Flow chart 1000 may begin at block 1010,when infrastructure remediation tool 620 determines if any of theperformance issue indicators specified in table 800 have a status of“active”. As described above, a performance issue indicator may be“active” if all the conditions of the indicator are satisfied. If aperformance issue indicator has a status of “active,” flow chart 1000may continue to block 1020 for that respective indicator. Otherwise,flow chart 1000 may remain at block 1010. In some embodiments,infrastructure remediation tool 620 could perform the operations atblock 1010 in accordance with a pre-determined schedule. For example,every X seconds (e.g., X=5, 30, 60, 90, 150), infrastructure remediationtool 620 may perform the operations at block 1010 to determine if any ofthe performance issue indicators specified in table 800 have a status of“active.”

At block 1020, infrastructure remediation tool 620 may determine whetherthe performance issue indicator from block 1010 has an associatedsubroutine. This could involve, for example, determining whether theperformance issue indicator from block 1010 has an associated entry intable 900. If the performance issue indicator from block 1010 has anassociated subroutine, flow chart 1000 may continue to block 1030.Otherwise, flow chart 1000 may continue to block 1050.

At block 1030, infrastructure remediation tool 620 may execute theassociated subroutine from block 1020. In line with the discussionabove, this could involve computational instance 322 executing objectcode, machine code, executable instructions, build instructions,configuration instructions, or the like. In some embodiments, block 1030could involve executing multiple subroutines that are associated withthe performance issue indicator from block 1010.

To determine if the subroutine actually succeeded in remediating theperformance issue, at block 1040, infrastructure remediation tool 620may determine whether the performance issue indicator from block 1010still has a status of “active.” If the indicator does not have a statusof “active” (meaning that the subroutine executed at block 1030succeeded in remediating the performance issue), flow chart 1000 maycontinue to back to block 1010. Otherwise, flow chart 1000 may continueto block 1050.

At block 1050, infrastructure remediation tool 620 could provide a GUIto an agent assigned to address the performance issue raised by theindicator from block 1010. The GUI may contain visualizations andtextual descriptions that assist the agent in understanding theperformance issue, including the data sources for the performance issueindicator, the subroutines associated with the performance issueindicator (if applicable), the severity of the performance issue, and soon. Alternatively, infrastructure remediation tool 620 could provide anindication of the performance issue raised by other means, such as phonecall, email, or text message.

Note that the blocks represented in FIG. 10 are used for the purpose ofexample and are not intended to be limiting with respect to theembodiments herein. The operations of infrastructure remediation tool620 may be highly configurable and may include more blocks, fewerblocks, or different blocks than those depicted in flow chart 1000. Insome cases, one or more blocks may be customized, or may otherwisedeviate from the exemplary description above.

FIG. 11 depicts message flow 1100, in accordance with exampleembodiments. In message flow 1100, a user from remote network managementplatform 320 configures one or more performance issue indicators and oneor more subroutines for infrastructure remediation tool 620. With theperformance issue indicators and subroutines configured, infrastructureremediation tool 620 could then determine if any of the configuredperformance issue indicators have conditions that are satisfied byoperational data received from data-database system 610. By way ofexample, message flow 1100 may utilize remote network managementplatform 320, infrastructure remediation tool 620, and dual-databasesystem 610 during operation. However, additional components, steps, orblocks, may be added to message flow 1100 without departing from thescope of this disclosure.

At step 1102, a user from remote network management platform 320provides one or more performance issue indicators and one or moresubroutines to infrastructure remediation tool 620. This may beaccomplished, for example, by a GUI provided by computational instance322 to a user from remote network management platform 320. The GUI mayinclude feature(s) for establishing performance issue indicators andsubroutines. Step 1102 could also be accomplished programmatically. Forexample, the user from remote network management platform 320 couldprovide the performance issue indicators and the subroutines bymodifying the source code of infrastructure remediation tool 620. Insome cases, step 1102 may be prompted by the user from remote networkmanagement platform 320, for example, by requesting the GUI fromcomputational instance 322.

At step 1104, infrastructure remediation tool 620 may receiveoperational data from components of dual-database system 610. Forinstance, infrastructure remediation tool 620 may receive operationaldata from master database engine 612, replicated database engine 614,routing engine 616, replication engine 618, a defragmentation enginedisposed within replication engine 618, or other components ofdual-database system 610. In some embodiments, infrastructureremediation tool 620 may store the received operational data in a datastructure suitable for time series data, for example, in round-robindatabase (RRD) files.

At step 1106, infrastructure remediation tool 620 may determine that oneof the performance issue indicators configured at step 1102 has: (i)conditions that are satisfied by the operational data received at step1104 and (ii) an associated subroutine. At step 1108, infrastructureremediation tool 620 may execute the associated subroutine.

At step 1110, infrastructure remediation tool 620 may receive additionaloperational data from components of dual-database system 610. In linewith the discussion above, the time period between receiving operationaldata at step 1104 and receiving operational data at step 1110 may be Xseconds (X=30, 60, 90, etc.), Y minutes (e.g., Y=1, 5, 10, 30, etc.), Zhours (e.g., Z=1, 2, 3, etc.) or some other time period.

At step 1112, infrastructure remediation tool 620 may perform anotherdetermination to establish that the performance issue indicatorsatisfied at step 1106 is still satisfied by the operational datareceived at step 1110. Since the indicator is still satisfied, thesubroutine executed at step 1108 did not succeed in remediating theperformance issue raised by the indicator. In line with the discussionabove, the time period between the determination at step 1106 and thedetermination at step 1112 may be X seconds (X=30, 60, 90, etc.), Yminutes (e.g., Y=1, 5, 10, 30, etc.), Z hours (e.g., Z=1, 2, 3, etc.) orsome other time period. Further, in some examples, the time periodbetween steps 1106 and 1112 is greater than the time period betweensteps 1104 and 1110. In other examples, the time period between steps1106 and 1112 is less than the time period between steps 1104 and 1110.

Because the performance issue was not remediated by the subroutineexecuted at step 1108, at step 1114, infrastructure remediation tool 620provides to an agent on remote network management platform 320 a GUI (orphone call, email, or text message) containing information on theperformance issue indicator satisfied at step 1106 as well asinformation on the subroutine that was executed at step 1108. Using thisinformation, the agent could take manual actions to address theperformance issue.

At step 1116, infrastructure remediation tool 620 could yet againreceive operational data from components of dual-database system 610. Atstep 1118, infrastructure remediation tool 620 may determine that one ofthe performance issue indicators configured at step 1102: (i) hasconditions that are satisfied by the operational data received at step1116 and (ii) does not have an associated subroutine. Thus, because nosubroutine can be executed, at step 1108, infrastructure remediationtool 620 could provide to an agent on remote network management platform320 a GUI (or phone call, email, or text message) containing informationon the performance issue indicator satisfied at step 1118. Using thisinformation, the agent could take manual actions to address theperformance issue.

Notably, the embodiments herein are not a mere automation of apreviously-known set of techniques and procedures. One of thedifficulties experienced in dual-database systems, such as the onesdescribed herein, is that the database engines, replication engines, androuting engines in a high-volume environment can fail in a surprisingnumber of ways. In the presence of these failures, it has been observedthat human agents undertake root cause analysis procedures in an ad-hocand subjective fashion. Each agent's personal experience may highlyinfluence the steps that the agent takes.

These embodiments eliminate this subjectivity by having the systemself-heal when it can. Based on the rules that associate conditions ofthe system to remediation subroutines, the system can self-correct inthe presence of most failures that occur in practice. To that point, ithas been observed that these embodiments can successfully address over90% of observed failures through various remediation techniques, such asrebooting a device, restarting an application, refreshing aconfiguration file, deleting files, and so on. Further, theseremediations occur rapidly, often within seconds or minutes of apotential or actual performance issue being discovered. Thus, theoverall performance, reliability, and fault-tolerance of the system isgreatly enhanced.

Further, the embodiments herein are not merely limited to dual-databasesystems, but could encompass any type of multi-database system. Forexample, some multi-database systems could include multiple replicateddatabase engines (e.g., 3, 4, 5, 10, 100, etc.) and multiple replicationengines (e.g., 3, 4, 5, 10, 100, etc.), with load balancers distributingqueries to each of the multiple replicated database engines. In suchexamples, an infrastructure remediation tool could be configured toreceive operational data from each of the multiple replicated databaseengines/multiple replication engines and process the operational data todetermine whether performance issues are occurring on any of themultiple replicated database engines/multiple replication engines. Ifthe infrastructure remediation tool determines that a performance issuehas occurred on a particular one of the multiple replicated databaseengines/multiple replication engines, the infrastructure remediationtool could then take automated measures to alleviate the performanceissue occurring on that particular replicated databaseengine/replication engine.

VI. Example Operations

FIG. 12 is a flow chart illustrating an example embodiment. The processillustrated by FIG. 12 may be carried out by a computing device, such ascomputing device 100, and/or a cluster of computing devices, such asserver cluster 200. However, the process can be carried out by othertypes of devices or device subsystems. For example, the process could becarried out by a computational instance of a remote network managementplatform or a portable computer, such as a laptop or a tablet device.

The embodiments of FIG. 12 may be simplified by the removal of any oneor more of the features shown therein. Further, these embodiments may becombined with features, aspects, and/or implementations of any of theprevious figures or otherwise described herein.

Block 1200 involves obtaining a set of indicators that are respectivelyassociated with performance issues that can occur in a database system,where each respective indicator defines one or more conditions that,when satisfied, cause the respective indicator to become active, wherethe database system contains a first database engine, a second databaseengine, and a replication engine configured to perform: (i) areplication process to replicate entries from the first database engineto the second database engine, and (ii) a defragmentation process todefragment the entries that are in the second database engine, and wherethe one or more conditions relate to the first database engine, thesecond database engine, the replication engine, the replication process,or the defragmentation process;

Block 1210 involves obtaining a set of mappings between: (i) at leastsome of the set of indicators, and (ii) remediation subroutines.

Block 1220 involves receiving operational data related to one or more ofthe first database engine, the second database engine, the replicationengine, the replication process, or the defragmentation process.

Block 1230 involves determining, based on the operational data and theconditions defined by the set of indicators, that a particular indicatoris active.

Block 1240 involves, responsive to the particular indicator beingactive, determining, based on the set of mappings, that the particularindicator has an associated remediation subroutine.

Block 1250 involves executing the associated remediation subroutine.

In some embodiments, the operational data is received from one or moreof the first database engine, the second database engine, or thereplication engine.

In some embodiments, each of the remediation subroutines addressesperformance issues related to its associated indicator from the set ofmappings.

Some embodiments involve (i) determining, based on the operational dataand the conditions defined by the set of indicators, that a secondparticular indicator is active; (ii) responsive to the second particularindicator being active, determining, based on the set of mappings, thatthe second particular indicator does not have an associated subroutine;and (iii) assigning a performance issue associated with the secondparticular indicator to an agent.

In some embodiments, assigning the performance issue associated with thesecond particular indicator to the agent involves (i) generating, fordisplay on a graphical user interface, a representation of theperformance issue and the one or more conditions associated with thesecond particular indicator; and (ii) transmitting the representationsas generated to a client device associated with the agent.

Some embodiments involve, after executing the associated remediationsubroutine, (i) receiving additional operational data related to one ormore of the first database engine, the second database engine, thereplication engine, the replication process, or the defragmentationprocess; (ii) determining, based on the additional operational data,that the particular indicator is still active; and (iii) assigning aperformance issue associated with the particular indicator to an agent.

Some embodiments involve (i) determining, based on the operational dataand the conditions defined by the indicators, that a second particularindicator is not active; (ii) after determining that the secondparticular indicator is not active, receiving additional operationaldata related to one or more of the first database engine, the seconddatabase engine, the replication engine, the replication process, or thedefragmentation process; (iii) determining, based on the additionaloperational data, that the second particular indicator is active; (iv)responsive to the second particular indicator being active, determining,based on the set of mappings, that the second particular indicator hasan associated second remediation subroutine; and (v) executing theassociated second remediation subroutine.

In some embodiments, receiving the additional operational data occursafter a first period of time from receiving the operational data anddetermining that the second particular indicator is active occurs aftera second period of time from determining that the second particularindicator is not active. In such embodiments, the second period of timemay be greater than the first period of time.

In some embodiments, obtaining the set of indicators involves (i)generating one or more graphical user interfaces with data entryelements for the one or more conditions of each of the set ofindicators; (ii) providing, to a client device, a representation of theone or more graphical user interfaces; and (iii) receiving, from theclient device and entered by way of the data entry elements, the one ormore conditions of each of the set of indicators.

Some embodiments involve a routing engine configured to receive databasequeries and perform a routing process to route the database queries toeither the first database engine or the second database engine. In suchembodiments, the operational data could include data related to one ormore of the routing engine or the routing process.

In some embodiments, the second database engine is a read-only replicaof the first database engine.

In some embodiments, the second database engine is column-orienteddatabase engine.

In some embodiments, the first data engine is an authoritative databaseengine for the database system.

In some embodiments, a system may include means for obtaining a set ofindicators that are respectively associated with performance issues thatcan occur in a database system, where each respective indicator definesone or more conditions that, when satisfied, cause the respectiveindicator to become active, where the database system contains a firstdatabase engine, a second database engine, and a replication engineconfigured to perform: (i) a replication process to replicate entriesfrom the first database engine to the second database engine, and (ii) adefragmentation process to defragment the entries that are in the seconddatabase engine, and where the one or more conditions relate to thefirst database engine, the second database engine, the replicationengine, the replication process, or the defragmentation process. Thesystem may also include means for obtaining a set of mappings between:(i) at least some of the set of indicators, and (ii) remediationsubroutines. The system may additionally include means for receivingoperational data related to one or more of the first database engine,the second database engine, the replication engine, the replicationprocess, or the defragmentation process. The system may further includemeans for determining, based on the operational data and the conditionsdefined by the set of indicators, that a particular indicator is active.The system may yet further include means for, responsive to theparticular indicator being active, determining, based on the set ofmappings, that the particular indicator has an associated remediationsubroutine. The system may also include means for executing theassociated remediation subroutine.

VII. Closing

The present disclosure is not to be limited in terms of the particularembodiments described in this application, which are intended asillustrations of various aspects. Many modifications and variations canbe made without departing from its scope, as will be apparent to thoseskilled in the art. Functionally equivalent methods and apparatuseswithin the scope of the disclosure, in addition to those describedherein, will be apparent to those skilled in the art from the foregoingdescriptions. Such modifications and variations are intended to fallwithin the scope of the appended claims.

The above detailed description describes various features and operationsof the disclosed systems, devices, and methods with reference to theaccompanying figures. The example embodiments described herein and inthe figures are not meant to be limiting. Other embodiments can beutilized, and other changes can be made, without departing from thescope of the subject matter presented herein. It will be readilyunderstood that the aspects of the present disclosure, as generallydescribed herein, and illustrated in the figures, can be arranged,substituted, combined, separated, and designed in a wide variety ofdifferent configurations.

With respect to any or all of the message flow diagrams, scenarios, andflow charts in the figures and as discussed herein, each step, block,and/or communication can represent a processing of information and/or atransmission of information in accordance with example embodiments.Alternative embodiments are included within the scope of these exampleembodiments. In these alternative embodiments, for example, operationsdescribed as steps, blocks, transmissions, communications, requests,responses, and/or messages can be executed out of order from that shownor discussed, including substantially concurrently or in reverse order,depending on the functionality involved. Further, more or fewer blocksand/or operations can be used with any of the message flow diagrams,scenarios, and flow charts discussed herein, and these message flowdiagrams, scenarios, and flow charts can be combined with one another,in part or in whole.

A step or block that represents a processing of information cancorrespond to circuitry that can be configured to perform the specificlogical functions of a herein-described method or technique.Alternatively or additionally, a step or block that represents aprocessing of information can correspond to a module, a segment, or aportion of program code (including related data). The program code caninclude one or more instructions executable by a processor forimplementing specific logical operations or actions in the method ortechnique. The program code and/or related data can be stored on anytype of computer readable medium such as a storage device including RAM,a disk drive, a solid state drive, or another storage medium.

The computer readable medium can also include non-transitory computerreadable media such as computer readable media that store data for shortperiods of time like register memory and processor cache. The computerreadable media can further include non-transitory computer readablemedia that store program code and/or data for longer periods of time.Thus, the computer readable media may include secondary or persistentlong term storage, like ROM, optical or magnetic disks, solid statedrives, or compact-disc read only memory (CD-ROM), for example. Thecomputer readable media can also be any other volatile or non-volatilestorage systems. A computer readable medium can be considered a computerreadable storage medium, for example, or a tangible storage device.

Moreover, a step or block that represents one or more informationtransmissions can correspond to information transmissions betweensoftware and/or hardware modules in the same physical device. However,other information transmissions can be between software modules and/orhardware modules in different physical devices.

The particular arrangements shown in the figures should not be viewed aslimiting. It should be understood that other embodiments can includemore or less of each element shown in a given figure. Further, some ofthe illustrated elements can be combined or omitted. Yet further, anexample embodiment can include elements that are not illustrated in thefigures.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purpose ofillustration and are not intended to be limiting, with the true scopebeing indicated by the following claims.

What is claimed is:
 1. A database system comprising: a first database, asecond database, and a replicator configured to perform: (i) areplication process to replicate entries from the first database to thesecond database, and (ii) a defragmentation process to defragment theentries that are in the second database; and one or more processorsconfigured to perform operations including: obtaining a set ofindicators that are respectively associated with performance issues thatcan occur in the database system, wherein each respective indicatordefines one or more conditions that cause the respective indicator tobecome active, and wherein the one or more conditions relate to thefirst database, the second database, the replicator, the replicationprocess, or the defragmentation process; obtaining a set of mappingsbetween: (i) at least some of the set of indicators, and (ii)remediation subroutines; receiving operational data related to one ormore of the first database, the second database, the replicator, thereplication process, or the defragmentation process; determining, basedon the operational data and the conditions defined by the set ofindicators, that a particular indicator is active; responsive to theparticular indicator being active, determining, based on the set ofmappings, that the particular indicator has an associated remediationsubroutine; and executing the associated remediation subroutine.
 2. Thedatabase system of claim 1, wherein the operational data is receivedfrom one or more of the first database, the second database, or thereplicator.
 3. The database system of claim 1, wherein each of theremediation subroutines addresses performance issues related to itsassociated indicator from the set of mappings.
 4. The database system ofclaim 1, wherein the operations further include: determining, based onthe operational data and the conditions defined by the set ofindicators, that a second particular indicator is active; responsive tothe second particular indicator being active, determining, based on theset of mappings, that the second particular indicator does not have anassociated subroutine; and assigning a performance issue associated withthe second particular indicator to an agent.
 5. The database system ofclaim 4, wherein assigning the performance issue associated with thesecond particular indicator to the agent comprises: generating, fordisplay on a graphical user interface, a representation of theperformance issue and the one or more conditions associated with thesecond particular indicator; and transmitting the representations asgenerated to a client device associated with the agent.
 6. The databasesystem of claim 1, wherein the operations further include: afterexecuting the associated remediation subroutine, receiving additionaloperational data related to one or more of the first database, thesecond database, the replicator, the replication process, or thedefragmentation process; determining, based on the additionaloperational data, that the particular indicator is still active; andassigning a performance issue associated with the particular indicatorto an agent.
 7. The database system of claim 1, wherein the operationsfurther include: determining, based on the operational data and theconditions defined by the indicators, that a second particular indicatoris not active; after determining that the second particular indicator isnot active, receiving additional operational data related to one or moreof the first database, the second database, the replicator, thereplication process, or the defragmentation process; determining, basedon the additional operational data, that the second particular indicatoris active; responsive to the second particular indicator being active,determining, based on the set of mappings, that the second particularindicator has an associated second remediation subroutine; and executingthe associated second remediation subroutine.
 8. The database system ofclaim 7, wherein receiving the additional operational data occurs aftera first period of time from receiving the operational data, whereindetermining that the second particular indicator is active occurs aftera second period of time from determining that the second particularindicator is not active, and wherein second period of time is greaterthan the first period of time.
 9. The database system of claim 1,wherein obtaining the set of indicators comprises: generating one ormore graphical user interfaces with data entry elements for the one ormore conditions of each of the set of indicators; providing, to a clientdevice, a representation of the one or more graphical user interfaces;and receiving, from the client device and entered by way of the dataentry elements, the one or more conditions of each of the set ofindicators.
 10. The database system of claim 1, further comprising: arouter configured to receive database queries and perform a routingprocess to route the database queries to either the first database orthe second database, wherein the operational data further comprises datarelated to one or more of the router or the routing process.
 11. Thedatabase system of claim 1, wherein the second database is a read-onlyreplica of the first database.
 12. The database system of claim 1,wherein the second database is column-oriented database.
 13. Thedatabase system of claim 1, wherein the first database is anauthoritative database for the database system.
 14. Acomputer-implemented method comprising: obtaining, by one or moreprocessors disposed within a database system, a set of indicators thatare respectively associated with performance issues that can occur inthe database system, wherein each respective indicator defines one ormore conditions that cause the respective indicator to become active,wherein the database system contains a first database, a seconddatabase, and a replicator configured to perform: (i) a replicationprocess to replicate entries from the first database to the seconddatabase, and (ii) a defragmentation process to defragment the entriesthat are in the second database, and wherein the one or more conditionsrelate to the first database, the second database, the replicator, thereplication process, or the defragmentation process; obtaining, by theone or more processors, a set of mappings between: (i) at least some ofthe set of indicators, and (ii) remediation subroutines; receiving, bythe one or more processors, operational data related to one or more ofthe first database, the second database, the replicator, the replicationprocess, or the defragmentation process; determining, by the one or moreprocessors and based on the operational data and the conditions definedby the set of indicators, that a particular indicator is active;responsive to the particular indicator being active, determining, by theone or more processors and based on the set of mappings, that theparticular indicator has an associated remediation subroutine; andexecuting, by the one or more processors, the associated remediationsubroutine.
 15. The computer-implemented method of claim 14, wherein theoperational data is received from one or more of the first database, thesecond database, or the replicator.
 16. The computer-implemented methodof claim 14, wherein each of the remediation subroutines addressesperformance issues related to its associated indicator from the set ofmappings.
 17. The computer-implemented method of claim 14, furthercomprising: determining, based on the operational data and theconditions defined by the set of indicators, that a second particularindicator is active; responsive to the second particular indicator beingactive, determining, based on the set of mappings, that the secondparticular indicator does not have an associated subroutine; andassigning a performance issue associated with the second particularindicator to an agent.
 18. The computer-implemented method of claim 14,further comprising: after executing the associated remediationsubroutine, receiving additional operational data related to one or moreof the first database, the second database, the replicator, thereplication process, or the defragmentation process; determining, basedon the additional operational data, that the particular indicator isstill active; and assigning a performance issue associated with theparticular indicator to an agent.
 19. The computer-implemented method ofclaim 14, further comprising: determining, based on the operational dataand the conditions defined by the indicators, that a second particularindicator is not active; after determining that the second particularindicator is not active, receiving additional operational data relatedto one or more of the first database, the second database, thereplicator, the replication process, or the defragmentation process;determining, based on the additional operational data, that the secondparticular indicator is active; responsive to the second particularindicator being active, determining, based on the set of mappings, thatthe second particular indicator has an associated second remediationsubroutine; and executing the associated second remediation subroutine.20. An article of manufacture including a non-transitorycomputer-readable medium, having stored thereon program instructionsthat, upon execution by one or more processors disposed within adatabase system, cause the one or more processors to perform operationscomprising: obtaining a set of indicators that are respectivelyassociated with performance issues that can occur in the databasesystem, wherein each respective indicator defines one or more conditionsthat cause the respective indicator to become active, wherein thedatabase system contains a first database, a second database, and areplicator configured to perform: (i) a replication process to replicateentries from the first database to the second database, and (ii) adefragmentation process to defragment the entries that are in the seconddatabase, and wherein the one or more conditions relate to the firstdatabase, the second database, the replicator, the replication process,or the defragmentation process; obtaining a set of mappings between: (i)at least some of the set of indicators, and (ii) remediationsubroutines; receiving operational data related to one or more of thefirst database, the second database, the replicator, the replicationprocess, or the defragmentation process; determining, based on theoperational data and the conditions defined by the set of indicators,that a particular indicator is active; responsive to the particularindicator being active, determining, based on the set of mappings, thatthe particular indicator has an associated remediation subroutine; andexecuting the associated remediation subroutine.